Blood biomarkers of outcomes after ischemic stroke

Introduction: Today, knowledge about predictors of stroke outcomes is limited and few studies have investigated blood biomarkers as predictors of outcomes after ischemic stroke, especially in the long-term. Aim: To investigate if there is an association between circulating concentrations of three novel biomarkers and long-term outcomes after ischemic stroke. Methods: The study population was derived from the Sahlgrenska Academy Study on Ischemic Stroke (SAHLSIS), which includes patients with ischemic stroke aged 18-69 years. Blood was drawn 3 months after the index stroke. Concentrations of neurofilament light chain (NFL) were analysed using a single-molecule array (Simoa) method. Concentrations of glial cell-derived neurotrophic factor family receptor a1 (GFRa1) and mesencephalic astrocytederived neurotrophic factor (MANF) were analysed using a proximity extension assay (PEA) technique. Associations to post-stroke outcomes assessed as the National Institutes of Health Stroke Scale (NIHSS) and the modified Rankin Scale (mRS) at a 7-year follow-up were examined using linear and logistic regression, respectively. Results: Concentrations of all three biomarkers were significantly higher in cases with poor (mRS 3-6) compared to good (mRS 0-2) outcome. All biomarkers were associated to NIHSS and mRS in the univariate analysis and the multivariate analysis adjusted for age and history of stroke. When additionally adjusting for stroke severity, i.e. baseline NIHSS, the association to mRS remained for all three biomarkers and the association to NIHSS remained for NFL and MANF. For GFRa1 and MANF, physical activity was also included in the model together with the covariates indicated above. In this model, the association for MANF and NIHSS remained. Conclusions: We identified three novel circulating biomarkers that were independently associated to neurological and functional outcomes after ischemic stroke. Further research is needed to design an assay with a set of biomarkers that effectively predicts post-stroke outcomes. Key words: ischemic stroke, functional outcomes, prognosis, biomarker